What Is So Special About Finland?

Students in science need to be trained not only in properly collecting data but as important, in correctly analyzing and drawing conclusions. Oftentimes, sweeping generalizations can be made haphazardly without examining closely the data and acknowledging complexities that may be present. This is especially a concern when it comes to basic education. There are a myriad of factors that influence learning outcomes. In this arena, it is very important to pay attention to details to avoid making exaggerated, oversimplified and misleading conclusions. One instance to which our attention is drawn is the average score of students in international standardized exams. A collaborative effort between Stanford's Graduate School of Education and the Economic Policy Institute recently produced an analysis, "What do international tests really show about US student performance?". The work demonstrates the danger of drawing conclusions simply from the average scores of students in international exams and using these conclusions as guides for education reform and policies. Most of their analysis illustrate that it is important to decompose the scores according to social class to see important findings that are hidden behind an aggregate or average number. By considering social classes and how these are represented in the sample student population that actually participated in the exam, it is estimated that the United States would have placed fourth in reading and tenth in math, to be compared with 14th and 25th standings, respectively, if only the raw average scores for each country are used. This adjustment comes from the oversampling of economically disadvantaged students in the United States. The international standards exams (TIMSS and PISA) include not only the scores of the students but also surveys. Results can therefore be disaggregated according to various factors that have been included in the survey. Examples are educational attainment of parents, hours of study, and others. Thus, with additional effort, scores of students in these exams can be examined under these various factors. Poverty is one factor that is arguably significant in learning outcomes. In the United States, poverty in schools can be correlated with the number of students eligible for free or reduced-price lunch. This system has a well-defined income level. Unfortunately, such is unique in the United States. Hence, one must choose a different measure to decompose the students' scores according to social class. One measure that Martin Carnoy and Richard Rothstein, the authors of the study, chose is the number of books in the household of each student. This is not a fool-proof ruler, but the number of books that can found inside a home strongly correlates with social class. It is one measure that is present in both TIMSS and PISA. Students can therefore be subdivided into various social classes according to this quantity:

The above table was downloaded from http://www.epi.org/publication/us-student-performance-testing/
With the above classification scheme, one can then view the scores of the students according to social class.

With the above segregation of scores, one can now compare the performance of students within the same group (social class according to number of books at home). One can look at the gap and it is quite obvious that the difference in scores between the lowest and highest social class group is highest in the United States. By the time one reaches Group 6, the highest social class, the difference between scores of the US students as compared to the top performing countries has diminished.  What is so special about Finland? In Group 1, the group with the lowest number of books in home, the lowest social class, Finland's students are on top in both reading and math. This is what "focusing on equity and not excellence" really means in Finland.


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